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.dockerignore

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+# Byte-compiled / optimized / DLL files
+**/__pycache__/**
+**/*.py[cod]
+
+# Git / CI
+.git/
+.github/
+
+# Editors / OS
+.DS_Store
+Thumbs.db
+
+# Local / Dev only
+*.bat
+*.sh
+*.crdownload
+pages/**
+PythonProject2/**
+
+# Large binaries / PDFs (adjust if needed)
+**/*.pdf
+
+# Node
+frontend/node_modules/
+
+# Build caches
+**/.cache/**
+
+

Dockerfile

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+# Multi-stage Dockerfile: build frontend, run FastAPI backend
+
+FROM node:20-alpine AS frontend-builder
+WORKDIR /app
+COPY frontend/package.json frontend/package-lock.json* ./
+RUN npm ci --no-audit --no-fund || npm install --no-audit --no-fund
+COPY frontend/ ./
+RUN npm run build
+
+FROM python:3.11-slim AS backend
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+# System deps (faiss-cpu needs libgomp1 on Debian)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libgomp1 \
+ && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application
+COPY . /app
+
+# Copy built frontend into expected path for static serving
+RUN mkdir -p /app/frontend/dist
+COPY --from=frontend-builder /app/dist /app/frontend/dist
+
+EXPOSE 7860
+
+# Hugging Face Spaces는 기본 PORT=7860을 사용합니다.
+CMD ["sh", "-c", "uvicorn api_server:app --host 0.0.0.0 --port ${PORT:-7860}"]
+
+

__init__.py

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+# 모임통장 AI 어드바이저 패키지

api_server.py

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+"""
+모바일 리액트 프런트에서 호출할 REST API 서버 (FastAPI)
+
+엔드포인트:
+- POST /api/advise            : 종합 상담 (금융+정보+복지)
+- POST /api/qa                : 자유 질문/챗봇 응답
+- GET  /api/welfare/search    : 복지정책 검색
+- GET  /api/products/search   : 금융상품 RAG 검색
+- GET  /health                : 상태 점검
+"""
+
+from fastapi import FastAPI, HTTPException, Query
+from fastapi.staticfiles import StaticFiles
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel, Field
+from typing import List, Optional, Dict, Any
+
+from agents.multi_agent_system import get_meeting_account_advisor
+from agents.welfare_advisor import WelfareAdvisor
+from agents.universal_info_advisor import get_universal_info_advisor
+from models.rag_system import get_kb_rag
+
+import pandas as pd
+import uvicorn
+
+
+app = FastAPI(title="KB 금융 AI Advisor API", version="1.0.0")
+
+# CORS (리액트/모바일 웹에서 호출 허용)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# 프런트엔드 정적 파일 제공 (frontend/dist가 있으면 자동 서빙)
+try:
+    import os
+    FRONT_DIST = os.path.join(os.path.dirname(__file__), "frontend", "dist")
+    if os.path.isdir(FRONT_DIST):
+        app.mount("/", StaticFiles(directory=FRONT_DIST, html=True), name="frontend")
+except Exception:
+    pass
+
+
+class UserInfo(BaseModel):
+    age_group: Optional[str] = None
+    family_type: Optional[str] = None
+    income_level: Optional[str] = None
+    region: Optional[str] = None
+
+
+class AdviseRequest(BaseModel):
+    purpose: str = Field(..., description="예: 스페인 어학연수, 결혼준비 등")
+    duration_months: int = Field(..., ge=1, le=120)
+    target_amount: int = Field(..., ge=1)
+    detailed_purpose: Optional[str] = None
+    current_amount: Optional[int] = 0
+    user_info: Optional[UserInfo] = None
+
+
+class AdviseResponse(BaseModel):
+    purpose_category: Optional[str]
+    financial_recommendation: Optional[str]
+    detailed_info: Optional[str]
+    welfare_recommendation: Optional[str]
+    comprehensive_advice: Optional[str]
+    progress_info: Optional[str] = None
+
+
+class QARequest(BaseModel):
+    question: str
+    detailed_context: Optional[str] = None
+
+
+class QAResponse(BaseModel):
+    answer: str
+    category: Optional[str] = None
+
+
+@app.get("/health")
+def health() -> Dict[str, Any]:
+    return {"status": "ok"}
+
+
+@app.post("/api/advise", response_model=AdviseResponse)
+def api_advise(req: AdviseRequest):
+    try:
+        advisor = get_meeting_account_advisor()
+        results = advisor.get_comprehensive_advice(
+            purpose=req.purpose,
+            duration_months=req.duration_months,
+            target_amount=req.target_amount,
+            detailed_purpose=req.detailed_purpose,
+        )
+
+        # 진행 현황 (current_amount 제공 시)
+        progress_info = None
+        if req.current_amount and req.current_amount > 0:
+            progress_info = advisor.get_savings_progress_tracking(
+                req.purpose,
+                req.duration_months,
+                req.target_amount,
+                req.current_amount,
+            )
+
+        # WelfareAdvisor에 사용자 정보 전달이 필요한 경우를 위해 보조 호출 (선택)
+        welfare_text = results.get("welfare_recommendation")
+        if (not welfare_text or "없습니다" in welfare_text) and req.user_info:
+            welfare = WelfareAdvisor().get_welfare_recommendations(
+                req.purpose, req.user_info.model_dump()
+            )
+            if welfare:
+                results["welfare_recommendation"] = welfare
+
+        return AdviseResponse(
+            purpose_category=results.get("purpose_category"),
+            financial_recommendation=results.get("financial_recommendation"),
+            detailed_info=results.get("detailed_info"),
+            welfare_recommendation=results.get("welfare_recommendation"),
+            comprehensive_advice=results.get("comprehensive_advice"),
+            progress_info=progress_info,
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/api/qa", response_model=QAResponse)
+def api_qa(req: QARequest):
+    try:
+        advisor = get_universal_info_advisor()
+        info = advisor.get_comprehensive_info(
+            purpose=req.question,
+            detailed_purpose=req.detailed_context,
+        )
+        return QAResponse(
+            answer=info.get("comprehensive_info", "답변을 생성하지 못했습니다."),
+            category=info.get("category"),
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/api/welfare/search")
+def api_welfare_search(
+    keyword: Optional[str] = Query(None, description="정책명/내용/대상 검색어"),
+    region: Optional[str] = Query(None, description="지역명 (예: 서울, 부산)"),
+    page: int = Query(1, ge=1),
+    size: int = Query(10, ge=1, le=100),
+):
+    try:
+        wa = WelfareAdvisor()
+        df = wa.welfare_data
+        if df.empty:
+            return {"total": 0, "items": []}
+
+        filtered = df.copy()
+        if keyword:
+            kw = keyword.strip()
+            mask = (
+                filtered["policy_name"].fillna("").str.contains(kw, case=False)
+                | filtered["service_content_detail"].fillna("").str.contains(kw, case=False)
+                | filtered["target_audience_description"].fillna("").str.contains(kw, case=False)
+            )
+            filtered = filtered[mask]
+
+        if region and region != "전체":
+            filtered = filtered[
+                (filtered["region_name"].fillna("").str.contains(region, case=False))
+                | (filtered["region_name"] == "전국")
+            ]
+
+        total = len(filtered)
+        start = (page - 1) * size
+        end = start + size
+        page_df = filtered.iloc[start:end]
+
+        items = []
+        for _, row in page_df.iterrows():
+            items.append(
+                {
+                    "policy_name": row.get("policy_name", ""),
+                    "governing_body": row.get("governing_body_name", ""),
+                    "target_audience": row.get("target_audience_description", ""),
+                    "service_content": row.get("service_content_detail", ""),
+                    "region": row.get("region_name", "전국"),
+                    "application_link": row.get("application_link", ""),
+                    "last_updated": row.get("last_updated", ""),
+                    "tags": row.get("target_audience_tags", ""),
+                }
+            )
+
+        return {"total": total, "items": items}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/api/products/search")
+def api_products_search(q: str = Query(..., description="검색 질의"), k: int = Query(5, ge=1, le=20)):
+    try:
+        rag = get_kb_rag()
+        results = rag.search_products(q, k=k) or []
+        return {"items": results}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+if __name__ == "__main__":
+    uvicorn.run("api_server:app", host="0.0.0.0", port=8000, reload=True)
+
+

config.py

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+"""
+모임통장 AI 에이전트 설정 파일
+"""
+import os
+from dotenv import load_dotenv
+
+# .env 파일이 있으면 로드 (선택사항)
+load_dotenv()
+
+# API Keys - 환경변수 우선, 필요 시 api_keys.py
+IGNORE_API_KEYS = os.getenv("IGNORE_API_KEYS", "0") == "1"
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
+
+if not IGNORE_API_KEYS and not GOOGLE_API_KEY:
+    try:
+        from api_keys import GOOGLE_API_KEY as FILE_GOOGLE_API_KEY, TAVILY_API_KEY as FILE_TAVILY_API_KEY
+        GOOGLE_API_KEY = GOOGLE_API_KEY or FILE_GOOGLE_API_KEY
+        TAVILY_API_KEY = TAVILY_API_KEY or FILE_TAVILY_API_KEY
+        print("✅ api_keys.py에서 API 키를 성공적으로 로드했습니다.")
+    except ImportError:
+        print("⚠️ api_keys.py를 찾을 수 없습니다. 환경변수에서 로드를 시도합니다.")
+
+SERPAPI_API_KEY = os.getenv("SERPAPI_API_KEY")
+
+# Model Settings
+GEMINI_MODEL_NAME = "gemini-2.0-flash-exp"
+
+# RAG Settings
+CHUNK_SIZE = 1000
+CHUNK_OVERLAP = 200
+TOP_K_RESULTS = 3
+
+# Data Paths
+KB_DATASET_PATH = "data/kb_products.csv"
+VECTOR_STORE_PATH = "data/vector_store"
+
+# Streamlit Settings
+PAGE_TITLE = "모임통장 AI 어드바이저"
+PAGE_ICON = "💰"

requirements.txt

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+langchain>=0.1.0
+langchain-google-genai>=1.0.0
+langchain-community>=0.0.35
+streamlit>=1.30.0
+pandas>=2.0.0
+numpy>=1.21.0
+faiss-cpu>=1.7.0
+python-dotenv>=1.0.0
+tavily-python>=0.3.0
+requests>=2.30.0
+sentence-transformers>=2.2.0
+fastapi>=0.111.0
+uvicorn[standard]>=0.30.0
+pydantic>=2.7.0